EP2394289B1 - Method of mass spectrometry - Google Patents

Method of mass spectrometry Download PDF

Info

Publication number
EP2394289B1
EP2394289B1 EP10711695.6A EP10711695A EP2394289B1 EP 2394289 B1 EP2394289 B1 EP 2394289B1 EP 10711695 A EP10711695 A EP 10711695A EP 2394289 B1 EP2394289 B1 EP 2394289B1
Authority
EP
European Patent Office
Prior art keywords
sample
predetermined position
mass
scan
peaks
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
EP10711695.6A
Other languages
German (de)
French (fr)
Other versions
EP2394289A1 (en
Inventor
Emmanuel Claude
Johannes Petrus Cornelis VISSERS
Keith Richardson
Marten F SNEL
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Micromass UK Ltd
Original Assignee
Micromass UK Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from GB0901933A external-priority patent/GB0901933D0/en
Priority claimed from GB0906465A external-priority patent/GB0906465D0/en
Application filed by Micromass UK Ltd filed Critical Micromass UK Ltd
Publication of EP2394289A1 publication Critical patent/EP2394289A1/en
Application granted granted Critical
Publication of EP2394289B1 publication Critical patent/EP2394289B1/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6848Methods of protein analysis involving mass spectrometry
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01JELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J49/00Particle spectrometers or separator tubes
    • H01J49/0004Imaging particle spectrometry
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01JELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J49/00Particle spectrometers or separator tubes
    • H01J49/0027Methods for using particle spectrometers

Definitions

  • the present invention relates to the field of mass spectrometry.
  • Mass spectrometric imaging is an emerging tool in post genomic sciences such as proteomics, lipidomics and metabolomics.
  • Lipidomics after genomics and proteomics, is a rapidly expanding research field that studies cellular lipidomes and the organisational hierarchy of lipid and protein constituents mediating life processes. Lipidomics is greatly facilitated by recent advances in, and novel applications of, electrospray ionization mass spectrometry (ESI/MS).
  • ESI/MS electrospray ionization mass spectrometry
  • Matrix Assisted Laser Desorption Ionization (MALDI) imaging mass spectrometry enables biomolecules to be analyzed directly from tissue sections, providing information on spatial distribution of analytes within the tissue sample. This involves the analysis of the differences in the chemical makeup of different areas of the substrate. Irradiation of areas of the substrate of interest by laser light in the presence of a matrix material produces ions that can be analysed by mass spectrometry, typically Time of Flight mass spectrometry (ToF).
  • TOF Time of Flight mass spectrometry
  • MALDI imaging data is typically arranged into different sections, a way of reducing the data complexity.
  • the ions from areas of the substrate that are in close relationship are added together to produce overall spectra for these sections within the substrate.
  • using this procedure means that data can be lost and that differences between the chemical make up of areas within each section of the substrate may not be identified.
  • a method of imaging a substrate is known from:
  • each predetermined position is identifiable by a set of coordinates such that the ionized sample is produced from said predetermined position.
  • the Mass Analyser is a Time of Flight Mass Analyser.
  • the ionisation of the sample is performed using MALDI.
  • the method further comprising the step of generating Ion mobility data for the ions produced at each predetermined position.
  • the method further comprises the step of generating MS and MS/MS data for the ions produced at each predetermined position.
  • the method further comprising the step of removing minor variations in spectral noise by subtraction of X% of the intensity of the peaks.
  • X is up to 15%, More Preferably X is in the range 1-10%. Most preferably X is in the range 3-7%.
  • the scan distributions are normalised to scale peaks relative to each other.
  • the method further comprises filtering said overall mass spectral data to perform background subtraction.
  • the substrate is a tissue sample.
  • the method is used for the analysis of information or products relating to drugs and drug metabolites within said tissue information.
  • the comparison of scan distributions comprises performing Principal Component Analysis.
  • the preferred embodiment of the current invention comprises the steps of:-
  • FIG 1 this shows mass spectrometric apparatus (1).
  • the apparatus comprises a housing (3) having a sample holder (5) for holding a sample plate (7).
  • the sample plate (7) has been loaded with a sample (9).
  • a laser (11) is disposed within the housing such that, when in use, the laser is orientated to irradiate the sample (9) at predetermined points upon the sample holder (5) with laser light.
  • ions (13) are formed from the predetermined points upon the sample. These ions are then transported into an analysis section of a mass spectrometer.
  • ions can be directed into an ion guide or ion tunnel for transporting into a mass analysis system.
  • suitable systems included a QToF type mass spectrometer or a Waters Synapt HDMS mass spectrometer.
  • the time of flight of the ions can be determined using a ToF mass analyser.
  • the ion mobility of the ions is measured in addition to their Time Of Flight. This may allow differentiation of ions of different species that may have the same mass.
  • ions produced can be transported directly into an axial time of flight drift tube using a pusher device within the ion source in a way similar to that in the Micromass MALDI Micro mass spectrometer,
  • the ions may be passed through a collision cell, and fragment ions produced within the collision cell may be analysed by the disclosed methods.
  • the ions may be passed through a drift cell, and the ion mobility of ions may be measured before analysis by the time of flight analyser.
  • the use of ion mobility data may be useful to distinguish between different ions of the same mass within the tissue sample under analysis by the disclosed methods.
  • the sample holder may be movable such that when using a stationary laser, the laser can irradiate different areas of the sample upon the sample holder.
  • the laser may be movable but the sample holder may be stationary so the laser can irradiate different areas of the sample upon the sample holder.
  • a location indicator should be assigned for each predetermined position within the sample. This may be a coordinate, scan number or any other form of location indicator.
  • the sample is a biological sample.
  • the sample may be adapted and designed for MALDI mass spectrometric analysis.
  • the sample may be adapted and designed for secondary ion mass spectrometry.
  • the sample may be designed for any other method of imaging of a sample.
  • the laser may be pulsed so that individual spots upon the sample may be irradiated consecutively and the spectra at each predetermined point may be produced from ions produced by either one, or multiple pulses of the laser.
  • the laser may continuously irradiate the sample whilst the sample and/or laser are moving with respect to each other.
  • the laser may irradiate ions for a substantial, though not continuous, proportion of the time whilst the sample and laser are moving with respect to each other.
  • the laser may be any type of suitable laser.
  • An example of a suitable laser is a solid state YaG laser.
  • An overall spectrum is generated by the addition of the spectra for each predetermined position that has been acquired across the whole of the sample.
  • each peak represents a particular analyte.
  • the peaks selected are the ⁇ >n' most intense peaks in the overall spectrum.
  • the peaks selected may be any peaks across the overall spectrum.
  • a 'scan distribution' is created for each selected analyte across the sample. This is created by plotting the intensity of each peak on the Y axis against a location indicator on the X axis for each point on the surface.
  • ion mobility dimension will be taken into account and a selected drift time range can be selected for each m/z peak. This can be done after an algorithm Apex 3D for example is applied to the data set.
  • the scan distributions can be smoothed and background 'noise' may be subtracted using mass spectral deconvolution programs.
  • spectral noise can be removed by the subtraction of a small percentage X of the intensity of the scan distribution can be produced.
  • X is less than 15%. More preferably X is in the range 1-10%. Most preferably X is in the range 3-7%.
  • the scan distribution can be normalised.
  • n is in the range 10-100000.
  • data relating to scan distributions that can be identified as correlating with other scan distributions s may be kept and data relating to scan distributions that can't be identified as correlating with other scan distributions may be excluded as desired.
  • the data produced by the disclosed methods may be imput into statistical software packages using multivariate statistics to identify relationships between different analytes across the substrate.
  • software packages suitable for this include Spotfire and Ez info.
  • the present invention utilises an unsupervised statistical approach to examine the entire dataset, rather than a more traditional approach where the dataset has been sectioned into different regions of interest. This does not involve the normal approach of obtaining "n" spectra from "n” regions and comparing those to highlight molecules more abundant in one region compared to another.
  • the distributions of molecules throughout the entire tissue section are compared to enable a statistical algorithm to group molecules which have similar scan distributions which represent similar localization. Rather than comparing MS spectra the method compares scan distributions for each of the molecules that is extracted where each scan represents a particular predetermined location.
  • MALDI imaging data obtained from the analyses of frozen mouse uterus tissue sections have been used to demonstrate the statistical approach.
  • Data from both MALDI MS imaging as well as MALDI IMS-MS imaging has been used to test the strategy.
  • the use of ion-mobility provides an extra dimension of separation for very complex sample datasets.
  • the data interpretation workflow starts with the extraction of the scan distribution for each m/z value. For each m/z value, the scan distribution represents its pixilated image without taking into account their spatial coordinate.
  • processing which may include; smoothing, background subtraction, removal of noise and/or normalization, the dataset can be interrogated using different multivariate statistical algorithms, such as clustering or Principal Component Analysis (PCA).
  • PCA Principal Component Analysis
  • PCA can rapidly group m/z values which exhibit similar distributions throughout the tissue, without prior knowledge. This approach easily facilitates, for example, the differentiation of exogenous molecules from endogenous molecules, as well as the identification of structural features within the image.

Description

  • The present invention relates to the field of mass spectrometry.
  • BACKGROUND ART
  • Mass spectrometric imaging is an emerging tool in post genomic sciences such as proteomics, lipidomics and metabolomics.
  • Lipidomics, after genomics and proteomics, is a rapidly expanding research field that studies cellular lipidomes and the organisational hierarchy of lipid and protein constituents mediating life processes. Lipidomics is greatly facilitated by recent advances in, and novel applications of, electrospray ionization mass spectrometry (ESI/MS).
  • Moreover, Matrix Assisted Laser Desorption Ionization (MALDI) imaging mass spectrometry enables biomolecules to be analyzed directly from tissue sections, providing information on spatial distribution of analytes within the tissue sample. This involves the analysis of the differences in the chemical makeup of different areas of the substrate. Irradiation of areas of the substrate of interest by laser light in the presence of a matrix material produces ions that can be analysed by mass spectrometry, typically Time of Flight mass spectrometry (ToF).
  • Limitation of MALDI imaging is the complexity of the data collected, especially in the case of a non- targeted, open platform experiment.
  • To overcome this limitation, MALDI imaging data is typically arranged into different sections, a way of reducing the data complexity. In this case the ions from areas of the substrate that are in close relationship are added together to produce overall spectra for these sections within the substrate. However, using this procedure means that data can be lost and that differences between the chemical make up of areas within each section of the substrate may not be identified.
  • A method of imaging a substrate is known from:
    • PAUL J. TRIM, SALLY J. ATKINSON, ALESSANDRA P. PRINCIVALLE, PETER S. MARSHALL, ANDREW WEST, MALCOLM R. CLENCH:
      • "Matrix-assisted laser desorption/ionisation mass spectrometry imaging of lipids in rat brain tissue with integrated unsupervised and supervised multivariant statistical analysis".
      • RAPID COMMUNICATIONS IN MASS SPECTROMETRY,
      • Vol. 22, no. 10, 17 April 2008 (2008-04-17), pages 1503-1509,
      • XP002587368,
      • DOI: 10.1002/rcm.3498
  • It is therefore desirable to find a method of analysis which will use all the data and differentiate between all the different areas of the substrate in an efficient way to identify information of interest relating to the sample.
  • SUMMARY OF THE INVENTION
  • A preferred embodiment of the current invention consists of a method of imaging of a substrate comprising the steps of:
    • Ionizing a sample of interest at multiple known positions upon the sample, producing a mass spectrum of the ionized sample at each of said multiple known positions using a Mass Spectrometer,
    • adding the mass spectra for each predetermined position to create an overall spectrum for the sample.
    • selecting a number of peaks within the overall spectrum,
    • creating a scan distribution for at least some of said selected peaks, and
    • comparing the scan distributions to identify correlations between different analytes within the sample.
  • Preferably, each predetermined position is identifiable by a set of coordinates such that the ionized sample is produced from said predetermined position.
  • Preferably, the Mass Analyser is a Time of Flight Mass Analyser.
  • Preferably the ionisation of the sample is performed using MALDI.
  • Preferably, the method further comprising the step of generating Ion mobility data for the ions produced at each predetermined position.
  • Preferably, the method further comprises the step of generating MS and MS/MS data for the ions produced at each predetermined position.
  • Preferably, the method further comprising the step of removing minor variations in spectral noise by subtraction of X% of the intensity of the peaks.
  • Preferably, X is up to 15%, More Preferably X is in the range 1-10%. Most preferably X is in the range 3-7%.
  • Preferably, the scan distributions are normalised to scale peaks relative to each other.
  • Preferably, the method further comprises filtering said overall mass spectral data to perform background subtraction.
  • Preferably, the substrate is a tissue sample.
  • Preferably, the method is used for the analysis of information or products relating to drugs and drug metabolites within said tissue information.
  • Preferably, the comparison of scan distributions comprises performing Principal Component Analysis.
  • Taking a "holistic" approach, numerous molecules including, endogenous (i.e. peptides, lipids) or exogenous (i.e. drug and its metabolites, matrix), can be detected within the tissue. When the data is presented as a series of images, one has to scan all masses to observe the differences, and similarities, between molecule localizations
  • An embodiment of the invention will now be described, by way of example, with reference to the accompanying drawings, in which :-
    • Figure 1 is a schematic view of a MALDI ion source
    DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
  • The preferred embodiment of the current invention comprises the steps of:-
    • Ionizing a sample of interest at multiple known positions upon the sample,
    • producing a mass spectrum of the ionized sample at each of said multiple known positions using a Mass Spectrometer,
    • creating an overall spectrum for the whole sample Select a number of peaks within the overall spectrum,
    • creating a scan distribution for at least some of said selected peaks, and
    • comparing the scan distributions to identify correlations between different analytes within the sample.
  • Turning to figure 1, this shows mass spectrometric apparatus (1). The apparatus comprises a housing (3) having a sample holder (5) for holding a sample plate (7). The sample plate (7) has been loaded with a sample (9). A laser (11) is disposed within the housing such that, when in use, the laser is orientated to irradiate the sample (9) at predetermined points upon the sample holder (5) with laser light. Upon the radiation of the sample with laser light, ions (13) are formed from the predetermined points upon the sample. These ions are then transported into an analysis section of a mass spectrometer.
  • In the preferred embodiment ions can be directed into an ion guide or ion tunnel for transporting into a mass analysis system. Examples of suitable systems included a QToF type mass spectrometer or a Waters Synapt HDMS mass spectrometer. In one embodiment of the invention, the time of flight of the ions can be determined using a ToF mass analyser. In another embodiment of the invention the ion mobility of the ions is measured in addition to their Time Of Flight. This may allow differentiation of ions of different species that may have the same mass.
  • In a less preferred embodiment, ions produced can be transported directly into an axial time of flight drift tube using a pusher device within the ion source in a way similar to that in the Micromass MALDI Micro mass spectrometer,
  • In one embodiment of the invention the ions may be passed through a collision cell, and fragment ions produced within the collision cell may be analysed by the disclosed methods.
  • In a further embodiment of the invention the ions may be passed through a drift cell, and the ion mobility of ions may be measured before analysis by the time of flight analyser. The use of ion mobility data may be useful to distinguish between different ions of the same mass within the tissue sample under analysis by the disclosed methods.
  • In one embodiment of the invention, the sample holder may be movable such that when using a stationary laser, the laser can irradiate different areas of the sample upon the sample holder. In an alternative embodiment of the invention the laser may be movable but the sample holder may be stationary so the laser can irradiate different areas of the sample upon the sample holder.
  • A location indicator should be assigned for each predetermined position within the sample. This may be a coordinate, scan number or any other form of location indicator.
  • In the preferred embodiment of the invention the sample is a biological sample.
  • In another embodiment of the invention the sample may be adapted and designed for MALDI mass spectrometric analysis.
  • In less preferred embodiments of the invention the sample may be adapted and designed for secondary ion mass spectrometry. In further embodiments of the invention the sample may be designed for any other method of imaging of a sample.
  • In one embodiment of the invention the laser may be pulsed so that individual spots upon the sample may be irradiated consecutively and the spectra at each predetermined point may be produced from ions produced by either one, or multiple pulses of the laser.
  • In an alternative embodiment of the invention the laser may continuously irradiate the sample whilst the sample and/or laser are moving with respect to each other.
  • In a further embodiment of the invention, the laser may irradiate ions for a substantial, though not continuous, proportion of the time whilst the sample and laser are moving with respect to each other.
  • The laser may be any type of suitable laser. An example of a suitable laser is a solid state YaG laser.
  • An overall spectrum is generated by the addition of the spectra for each predetermined position that has been acquired across the whole of the sample.
  • Once the overall spectrum has been generated, all peaks or a number of the peaks can be selected for further analysis. Each peak represents a particular analyte.
  • In the most preferred embodiment, the peaks selected are the <λ>n' most intense peaks in the overall spectrum.
  • In less preferred embodiments the peaks selected may be any peaks across the overall spectrum.
  • A 'scan distribution' is created for each selected analyte across the sample. This is created by plotting the intensity of each peak on the Y axis against a location indicator on the X axis for each point on the surface.
  • In a preferred embodiment, ion mobility dimension will be taken into account and a selected drift time range can be selected for each m/z peak. This can be done
    after an algorithm Apex 3D for example is applied to the data set.
  • In the preferred embodiment the scan distributions can be smoothed and background 'noise' may be subtracted using mass spectral deconvolution programs.
  • In the preferred embodiment, spectral noise can be removed by the subtraction of a small percentage X of the intensity of the scan distribution can be produced. Preferably X is less than 15%. More preferably X is in the range 1-10%. Most preferably X is in the range 3-7%.
  • In the preferred embodiment the scan distribution can be normalised.
  • The scan distributions of the 'n' selected peaks are then compared to identify correlations between the different analytes within the sample. Preferably, n is in the range 10-100000.
  • In one embodiment data relating to scan distributions that can be identified as correlating with other scan distributions s may be kept and data relating to scan distributions that can't be identified as correlating with other scan distributions may be excluded as desired.
  • In one embodiment the data produced by the disclosed methods may be imput into statistical software packages using multivariate statistics to identify relationships between different analytes across the substrate. Examples of software packages suitable for this include Spotfire and Ez info.
  • The present invention utilises an unsupervised statistical approach to examine the entire dataset, rather than a more traditional approach where the dataset has been sectioned into different regions of interest. This does not involve the normal approach of obtaining "n" spectra from "n" regions and comparing those to highlight molecules more abundant in one region compared to another. In the present method, the distributions of molecules throughout the entire tissue section are compared to enable a statistical algorithm to group molecules which have similar scan distributions which represent similar localization. Rather than comparing MS spectra the method compares scan distributions for each of the molecules that is extracted where each scan represents a particular predetermined location.
  • Preliminary data
  • MALDI imaging data obtained from the analyses of frozen mouse uterus tissue sections have been used to demonstrate the statistical approach. Data from both MALDI MS imaging as well as MALDI IMS-MS imaging has been used to test the strategy. The use of ion-mobility provides an extra dimension of separation for very complex sample datasets. The data interpretation workflow starts with the extraction of the scan distribution for each m/z value. For each m/z value, the scan distribution represents its pixilated image without taking into account their spatial coordinate. After processing which may include; smoothing, background subtraction, removal of noise and/or normalization, the dataset can be interrogated using different multivariate statistical algorithms, such as clustering or Principal Component Analysis (PCA). PCA can rapidly group m/z values which exhibit similar distributions throughout the tissue, without prior knowledge. This approach easily facilitates, for example, the differentiation of exogenous molecules from endogenous molecules, as well as the identification of structural features within the image.
  • OTHER EMBODIMENTS
  • It will be apparent that various modifications may be made to the particular embodiments discussed above without departing from the scope of the invention.

Claims (15)

  1. A method of analysis of data produced from the imaging of a substrate comprising the steps of:
    ionizing a sample of interest at multiple predetermined positions upon the sample,
    producing a mass spectrum of the ionized sample at each of said multiple predetermined positions using a Mass Analyser,
    adding the mass spectra for each predetermined position to create an overall spectrum for the sample,
    selecting a number of peaks within the overall spectrum,
    creating a scan distribution for at least some of said selected peaks, and
    comparing the scan distributions to identify correlations between different analytes within the sample .
  2. A method as claimed in claim 1 wherein each predetermined position is identifiable by a set of coordinates such that the ionized sample is produced from said predetermined position.
  3. A method as claimed in claims 1 or 2 wherein said Mass Analyser is a Time of Flight Mass Analyser.
  4. A method as claimed in claims 1-3 wherein said ionisation of sample is performed using MALDI.
  5. A method as claimed in any of the preceding claims, further comprising the step of generating Ion Mobility data for the ions produced at each predetermined position.
  6. A method as claimed in any of the preceding claims, further comprising the step of generating MSMS data for the ions produced at each predetermined position
  7. A method as claimed in any of the preceding claims, further comprising the step of removing minor variations in spectral noise by subtraction of X% of the intensity of the peaks
  8. A method as claimed in claim 7, wherein X is a value up to 15%
  9. A method as claimed in claim 8, wherein X is in the range 1-10%.
  10. A method as claimed in claim 9, wherein X is in the range 3-7%
  11. A method as claimed in any of the preceding claims, wherein said scan distributions are normalized to scale peaks relative to each other.
  12. A method as claimed in any of the preceding claims, further comprising filtering said overall mass spectral data to perform background subtraction.
  13. A method as claimed in any of the preceding claims, wherein the substrate is a tissue sample.
  14. A method as claimed in claim 13 for the analysis of information or products relating to drugs and drug metabolites within said tissue information
  15. A method as claimed in any preceding claim wherein said comparison of scan distributions comprises performing Principal Component Analysis.
EP10711695.6A 2009-02-06 2010-02-08 Method of mass spectrometry Active EP2394289B1 (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
GB0901933A GB0901933D0 (en) 2009-02-06 2009-02-06 Method and apparatus for MALDI imaging
GB0906465A GB0906465D0 (en) 2009-04-15 2009-04-15 Method of mass spectrometry
US18170809P 2009-05-28 2009-05-28
PCT/GB2010/050194 WO2010089611A1 (en) 2009-02-06 2010-02-08 Method of mass spectrometry

Publications (2)

Publication Number Publication Date
EP2394289A1 EP2394289A1 (en) 2011-12-14
EP2394289B1 true EP2394289B1 (en) 2017-12-27

Family

ID=42227611

Family Applications (1)

Application Number Title Priority Date Filing Date
EP10711695.6A Active EP2394289B1 (en) 2009-02-06 2010-02-08 Method of mass spectrometry

Country Status (4)

Country Link
US (1) US8426808B2 (en)
EP (1) EP2394289B1 (en)
JP (1) JP2012517588A (en)
WO (1) WO2010089611A1 (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102010009853B4 (en) * 2010-03-02 2012-12-06 Bruker Daltonik Gmbh Determination of tissue states by means of imaging mass spectrometry
JP5408107B2 (en) * 2010-11-10 2014-02-05 株式会社島津製作所 MS / MS mass spectrometer and program for the same
JP5751824B2 (en) * 2010-12-20 2015-07-22 キヤノン株式会社 Information acquisition method
AU2013267976B2 (en) 2012-05-29 2016-06-02 Biodesix, Inc. Deep-MALDI TOF mass spectrometry of complex biological samples, e.g., serum, and uses thereof
AU2013382989B2 (en) 2013-03-22 2018-06-07 Eth Zurich Laser ablation cell
CA2969251C (en) * 2014-12-08 2023-08-15 Arash Zarrine-Afsar System and method for enhanced mass spectrometry imaging
US11266383B2 (en) 2015-09-22 2022-03-08 University Health Network System and method for optimized mass spectrometry analysis
JP6569805B2 (en) * 2016-05-10 2019-09-04 株式会社島津製作所 Imaging mass spectrometer

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7057168B2 (en) * 1999-07-21 2006-06-06 Sionex Corporation Systems for differential ion mobility analysis
GB0329554D0 (en) * 2003-12-22 2004-01-28 Micromass Ltd Mass spectrometer
US7365309B2 (en) * 2003-12-22 2008-04-29 Micromass Uk Limited Mass spectrometer
JP4470505B2 (en) * 2004-02-04 2010-06-02 株式会社島津製作所 Data processing equipment for chromatographic mass spectrometry
DE102004037512B4 (en) * 2004-08-03 2012-11-08 Bruker Daltonik Gmbh Mass spectrometric tissue state differentiation
CA2546667A1 (en) * 2005-06-03 2006-12-03 F. Hoffmann-La Roche Ag In situ biomarker identification
JP4952788B2 (en) * 2007-04-04 2012-06-13 株式会社島津製作所 Mass spectrometry data analysis method and apparatus
JP5050705B2 (en) * 2007-07-24 2012-10-17 株式会社島津製作所 Mass spectrometer
JP4973360B2 (en) * 2007-07-24 2012-07-11 株式会社島津製作所 Mass spectrometer

Also Published As

Publication number Publication date
EP2394289A1 (en) 2011-12-14
US8426808B2 (en) 2013-04-23
JP2012517588A (en) 2012-08-02
WO2010089611A1 (en) 2010-08-12
US20120326019A1 (en) 2012-12-27

Similar Documents

Publication Publication Date Title
EP2394289B1 (en) Method of mass spectrometry
US9343278B2 (en) Data independent acquisition of product ion spectra and reference spectra library matching
JP7014293B2 (en) Acquisition and analysis method of mass spectrum data
JP6597909B2 (en) Mass spectrometry data processor
CN109642890B (en) Imaging mass spectrometry data processing device and method
WO2017195271A1 (en) Imaging mass spectrometer
GB2503538A (en) Methods of associating parent and daughter ions from a sample
Mascini et al. Protein identification in mass-spectrometry imaging
Ye et al. From pixel to voxel: a deeper view of biological tissue by 3D mass spectral imaging
Fletcher et al. Evaluating the challenges associated with time-of-fight secondary ion mass spectrometry for metabolomics using pure and mixed metabolites
EP3254301B1 (en) Lipid screening platform allowing a complete solution for lipidomics research
US9230785B2 (en) Ion trap mass spectrometer and ion trap mass spectrometry method
Cho et al. Combining MALDI-TOF and molecular imaging with principal component analysis for biomarker discovery and clinical diagnosis of cancer
EP3745407A1 (en) Operating a mass spectrometer utilizing a promotion list
CN109416343B (en) Chemical-based composition of collision cross-section fragment ions
CN116263442A (en) Mass spectrometry data independent analysis method with improved efficiency
Shi et al. Peptide charge state determination of tandem mass spectra from low-resolution collision induced dissociation
Bielow et al. Bioinformatics for qualitative and quantitative proteomics
EP3739328A1 (en) Method for identifying proteins
Meier Data acquisition methods for next-generation mass spectrometry-based proteomics
Adams et al. Mass Spectrometry and Chemical Imaging
JP2024515586A (en) Biological Identification Using Low Resolution Tandem Mass Spectrometry
Mobility–Mass 13 Profiling and Imaging
Hochrein et al. Atmospheric Ionization Mass Spectrometry Capabilities at Sandia National Labs.

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20110905

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO SE SI SK SM TR

DAX Request for extension of the european patent (deleted)
RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: MICROMASS UK LIMITED

17Q First examination report despatched

Effective date: 20150708

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

INTG Intention to grant announced

Effective date: 20171027

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO SE SI SK SM TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: CH

Ref legal event code: EP

REG Reference to a national code

Ref country code: AT

Ref legal event code: REF

Ref document number: 958984

Country of ref document: AT

Kind code of ref document: T

Effective date: 20180115

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: DE

Ref legal event code: R096

Ref document number: 602010047633

Country of ref document: DE

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: NO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180327

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20171227

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG4D

REG Reference to a national code

Ref country code: AT

Ref legal event code: MK05

Ref document number: 958984

Country of ref document: AT

Kind code of ref document: T

Effective date: 20171227

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180328

Ref country code: HR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: LV

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: BG

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180327

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: ES

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: CZ

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: CY

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: EE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: SK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180427

Ref country code: RO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: AT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: IT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: SM

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: PL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

REG Reference to a national code

Ref country code: CH

Ref legal event code: PL

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

REG Reference to a national code

Ref country code: DE

Ref legal event code: R097

Ref document number: 602010047633

Country of ref document: DE

PLBE No opposition filed within time limit

Free format text: ORIGINAL CODE: 0009261

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT

REG Reference to a national code

Ref country code: IE

Ref legal event code: MM4A

REG Reference to a national code

Ref country code: BE

Ref legal event code: MM

Effective date: 20180228

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: DK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: LI

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180228

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180208

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180228

REG Reference to a national code

Ref country code: FR

Ref legal event code: ST

Effective date: 20181031

26N No opposition filed

Effective date: 20180928

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: FR

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180228

Ref country code: SI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: BE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180228

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: MT

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20180208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: TR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: HU

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT; INVALID AB INITIO

Effective date: 20100208

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20171227

Ref country code: MK

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20171227

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: GB

Payment date: 20230121

Year of fee payment: 14

Ref country code: DE

Payment date: 20230119

Year of fee payment: 14

P01 Opt-out of the competence of the unified patent court (upc) registered

Effective date: 20230609

P02 Opt-out of the competence of the unified patent court (upc) corrected

Effective date: 20230619